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Prediction of Heat Transfer Coefficient and Pressure Drop in Wire Heat Exchanger Working with R-134a and R-600a
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An experimental and theoretical works were carried out to model the wire condenser in the domestic refrigerator by calculating the heat transfer coefficient and pressure drop and finding the optimum performance. The two methods were used for calculation, zone method, and an integral method. The work was conducted by using two wire condensers with equal length but different in tube diameters, two refrigerants, R-134a and R-600a, and two different compressors matching the refrigerant type. In the experimental work, the optimum charge was found for the refrigerator according to ASHRAE recommendation. Then, the tests were done at 32˚C ambient temperature in a closed room with dimension (2m*2m*3m). The results showed that the average heat transfer coefficient for the R-600a was higher than the R-134a, so the length of the wire tube was longer with R-134a than R-600a. The pressure drop for the smaller tube diameter was higher than the other tube. The second law thermodynamic efficiency was higher for R-600a, which reached 41%.  The entropy generation minimization analysis showed that the R-600a refrigerant type and smaller tube diameter are approached the optimum point.

 

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Theoretical Investigation of the Effects of some Geometrical Parameters on the Performance of Wire-Plate Electrostatic Precipitator
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     Some geometric parameters affecting the performance of a wire-plate electrostatic precipitator (ESP) are investigated theoretically. A numerical model was built to investigate the influence of the discharge wire size, wire separation, collector plates spacing, and roughness factor on the ESP performance. The results show that thinner wires emit higher current than larger ones at the same applied voltage, which would be suitable for low voltage power supply to generate the desired current density at the collecting electrodes. The results also show that, as the discharge electrodes get closer, the corona gets suppressed, resulting in a diminished corona current flow. On the other hand, as the distance between elect

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Publication Date
Sun May 14 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Calculate of the Rate Constant of Electron Transfer in TiO2 – Safranine Dye System
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         A theoretical calculations of the rate constant of electron transfer (ET) in a dye – semiconductor system with variety solvent are applied on system contains safranineT dye with TiO2 in many solvents like water, 1-propanol, Formamide, Acetonitrile and Ethanol.

    A matlap program has been written to evaluate many parameters such that, the solvent reorganization energy, effective free energy, activation free energy, coupling matrix element and the rate constant of electron transfer.

    The results of the rate constant of electron transfer calculated theoretically are in a good agreement with experimental and theoretical value

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sun Jun 03 2018
Journal Name
Baghdad Science Journal
Influence of Lead Exposure in the Expression of Calmodulin – Related Genes: A Preliminary Study on Workers Working in Industry of Batteries, In Iraq
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Most pathological effects of lead on the body are due to ability of lead to bind with important cellular molecules of various tissues and organs leading to formation abnormal molecules and thus to emergence of pathological conditions. To evaluation the risk to the health status of Iraqi workers who work in the batteries industry, expression of three types of calmodulin related genes were examined. Blood samples were collected from worker working in Iraqi industry of batteries (located in Al-Waziriya), then RNAs extraction were done thereby gene expression for Calcium/Calmodulin- dependent protein kinase2 (CaMKK2), C-X-C Chemokine receptor 4 (CXCR4) and mitogen activated protein kinase kinase 6 (MAP2K6) was done for each sample by using RT-q

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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Accurate MHD Flux Solutions of a Viscose Fluid and Generalized Burgers' Model fluxwithin an Annular Pipe Under Sinusoidal Pressure
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The aim of this work presents the analytical studies of both the magnetohydrodynamic (MHD) flux and flow of the non-magnetohydro dynamic (MHD) for a fluid of generalized Burgers’ (GB) withinan annular pipe submitted under Sinusoidal  Pressure (SP)gradient. Closed beginning velocity's' solutions are taken by performing the finite Hankel transform (FHT) and Laplace transform (LT) of the successivefraction derivatives. Lastly, the figures were planned to exhibition the transformations effects of different fractional parameters (DFP) on the profile of velocity of both flows.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
The Effective of Pressure and Sintering Temperature for Hardness Characteristics of Shape Memory Alloy by Using Taguchi Technique
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This paper presents the Taguchi approach for optimization of hardness for  shape memory alloy (Cu-Al-Ni) . The influence of  powder metallurgy parameters on hardness has been investigated. Taguchi technique and ANOVA were used for analysis. Nine experimental runs based on Taguchi’s L9 orthogonal array were performed (OA),for two parameters was study (Pressure and sintering temperature) for three different levels (300 ,500 and 700) MPa ,(700 ,800 and  900)oC respectively . Main effect, signal-to-noise (S/N) ratio was study, and analysis of variance (ANOVA) using  to investigate the micro-hardness characteristics of the shape memory alloy .after application the result of study shown the hei

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Mathematical Modeling of a Hollow Fiber Module Used in Pressure-Retarded Osmosis Process
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   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The eff

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Electrochemical Science And Technology
Simultaneous Removal of Cadmium and Copper from a Binary Solution by Cathodic Deposition Using a Spiral-Wound Woven Wire Meshes Packed Bed Rotating Cylinder Electrode
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Compare Prediction by Autoregressive Integrated Moving Average Model from first order with Exponential Weighted Moving Average
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

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